Performance Analysis of Reservation and Contention-Based Hybrid MAC for Wireless Networks
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Bibliographic record
Abstract
Hybrid media access control (MAC) protocols use reservation and contention-based approaches simultaneously, so they can provide satisfactory quality-of-service to multimedia applications by resource reservation, and achieve high resource utilization with multiplexing gain during the contention periods. However, reservation can significantly affect the behavior of the contention-based access. How to split channel time between reservation periods and contention periods and how to adjust the contention scheme for hybrid MAC are important, open issues. In this paper, an analytical model for the hybrid MAC with saturated traffic is first proposed and then extended to the unsaturated traffic case. Based on the mean value analysis, the proposed models give the average frame service time and throughput for the contention-based MAC with the presence of reserved channel periods. They are also applicable to online admission control due to their low computational complexity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it